Assessing Public Transportation Accessibility Equity and Scoring Transit Lines Based on Their Contribution: An Open-Data Based Approach

In order to encourage people to use alternative transport solutions while reducing the disproportional use of cars, studies that could provide relevant information to stakeholders and policymakers are required. This is due to the excessive use of cars and its negative externalities, such as traffic congestion and the production of high levels of carbon dioxide (CO2). Therefore, one strategy is to improve public transport by providing a fair level of access to it for the people to encourage them to have a multimodal behavior regarding transport. This thesis proposes a methodology to assess public transportation accessibility inequity of land parcels served by transit systems in metropolitan areas. The methodology is based on the classic analysis tools of Lorenz curves and Gini indices, but the novelty resides in the fact that it can be easily applied in an automated way to several cities around the world, with no need for customized data treatment. Indeed, our equity metrics can be computed solely relying on open data, publicly available in a standardized form. We showcase our method by studying public transportation territorial equity in Paris, Madrid, Sydney, and Boston, and compare our findings with another recently proposed approach. The above issue is related to the configuration of the transit offer in urban areas. Current transit suffers from an evident inequity: the level of service of transit in the suburbs is much less satisfying than in city centers, especially when budget constraints are tight. Consequently, private cars are still the dominant transportation mode for suburban people, which results in congestion and pollution. To achieve sustainability goals, transit should be (re)designed, placing equity among the main optimization objectives. To this aim, it is necessary to (i) quantify the "level of equity" of transit and (ii) identify the transit lines that are the most important to equity, which would then be the ones where the operator should invest the most in increasing service level (frequency or coverage) in order to reduce inequity in the system. To the best of our knowledge, we are the first to tackle (ii). We propose efficient computational methods that rely solely on open data, allowing us to analyze the whole transit networks in Aachen, Berlin, Budapest, Helsinki, Manchester, Turin, and Vienna. Our method can be used to guide large-scale iterative optimization algorithms toward the goal of improving accessibility equity.